Documents can be found:
- Google Scholar
- Researchgate


Publications
◇ Myungin Lee, Jongwoo Yim, "AlloThresher: Multimodal Granular Synthesizer," International Computer Music Conference (ICMC), July 2024.

  - Link: Paper

 

◇ Jamie Ngoc Dinh,  You-Jin Kim, Myungin Lee, "FractalBrain: Neuro-interactive VR using EEG for Mindfulness," CHI Interactivity, May 2024.
  - Link: Paper

◇ You-Jin Kim, Myungin Lee, Marko Peljhan, JoAnn Kuchera-Morin, Tobias Höllerer, "Spatial Orchestra: Locomotion Music Instruments through Spatial Exploration," CHI Interactivity, May 2024.
  - Link: Paper

◇ Myungin Lee, Sabina Hyoju Ahn, Yoojin Oh, JoAnn Kuchera-Morin, "Parasitic signals: Multimodal Sonata for Real-time Interactive Simulation of the SARS-CoV-2 Virus," IEEE VIS Arts Program, 2023.

  - Link: Paper

◇ Myungin Lee, “Coherent Digital Multimodal Instrument Design and the Evaluation of Crossmodal Correspondence," Ph.D. dissertation, August., 2023.

  - Link: Paper

◇ Myungin Lee, “Entangled: A Multi-Modal, Multi-User Interactive Instrument in Virtual 3D Space Using the Smartphone for Gesture Control," New Interfaces for Musical Expression (NIME'21), Jun., 2021.

  - Link: Paper

◇ Myungin Lee, “A Multi-User Interactive Instrument in the 3D Space Using the Gesture of Smartphones,” Korea Electro-Acoustic Music Society's Annual Conference (KEAMSAC), Oct., 2019.

◇ Myungin Lee, "Deep neural network based music source conducting system," International Computer Music Conference (ICMC), 2018.

  - Link: Paper

◇ Myungin Lee, Joon-Hyuk Chang, "Deep neural network based blind estimation of reverberation time based on multi-channel microphones," Acta Acustica united with Acustica, 2018.
  - Link: Paper

◇ Myungin Lee, Joon-Hyuk Chang, “Blind Estimation of Reverberation Time on Multi-Channel Microphone using Deep Neural Network,” Master’s thesis, Feb., 2017.

◇ Myungin Lee, Joon-Hyuk Chang, “Blind Estimation of Reverberation Time using Deep Neural Network,” IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), Beijing, China, Sep., 2016.
  - Link: Paper​

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◇ Jeehye Lee, Myungin Lee, Joon-Hyuk Chang, “Ensemble of Jointly Trained Deep Neural Network-Based Acoustic Models for Reverberant Speech Recognition,” arXiv:1608.04983, 2016.

Domestic 

◇ Myungin Lee, Joon-Hyuk Chang, "A study of room acoustics estimation using neural network," Korea Speech Communication and Signal Processing, The Acoustical Society of Korea, pp. 30, August, 2016.

◇ Tae-jun Park, Bong-Ki Lee, Myungin Lee, Joon-Hyuk Chang, "Integrated acoustic echo and background noise suppression based on data-driven method, Korea Speech Communication and Signal Processing, The Acoustical Society of Korea, Vol. 32, No. 1, pp. 145-146, August, 2015.

◇ Songkyu Park, Jihwan Park, Myungin Lee, Joon-Hyuk Chang, "A study of speech enhancement using microphone array structure," Korea Speech Communication and Signal Processing, The Acoustical Society of Korea, Vol. 32, No. 1, pp. 153-155, August, 2015.

◇ Myungin Lee, Jihwan Park, Songkyu Park, Joon-Hyuk Chang,, "A study of crosstalk cancellation efficiency in reverberant environment," Korea Speech Communication and Signal Processing, The Acoustical Society of Korea, Vol. 32, No. 1, pp. 167-169, August, 2015.


Patent Activity
◇ Multichannel microphone-based reverberation time estimation method and device which use deep neural network,
   WO Patent WO2018111038A1, 2018.

◇ Multichannel microphone-based reverberation time estimation method and device which use deep neural network,
   US Patent US10854218B2, 2018.

◇ Method and Apparatus for Estimating Reverberation Time based on Multi-Channel Microphone using Deep Neural Network, Korean Patent Application Publication No. 10-2016-0171359, 2016.